Using Llama 4 Scout 17B-16E Instruct on GCP Vertex AI
Implementation guide · Llama 4 · AI at Meta
GCP Vertex AI exposes Llama 4 Scout 17B-16E Instruct through model ID llama-4-scout-17b-16e-instruct. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-09. Next refresh: weekly.
Quick Start
- 1
- 2Use the GCP Vertex AI SDK or REST API to call
llama-4-scout-17b-16e-instruct— see the documentation for request format. - 3
Code Examples
pip install google-cloud-aiplatformGOOGLE_CLOUD_PROJECTllama-4-scout-17b-16e-instructFor Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".
import os
import vertexai
from vertexai.generative_models import GenerativeModel
# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("llama-4-scout-17b-16e-instruct")
response = model.generate_content("Hello")
print(response.text)Pricing on GCP Vertex AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.65 |
Capabilities
About Llama 4 Scout 17B-16E Instruct
Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.